As photovoltaic (PV) solar power systems continue to increase in number and in scale, harvesting and managing power efficiently has become more challenging. Equally as challenging is the management of PV power installations on a national level via a “smart grid”. In particular, it is desirable to increase the demand for renewable energy, to supplement and/or replace energy produced via fossil fuels. Enhancing PV power use, however, requires reduction in the production cost per kilowatt hour and reduction in utility transaction costs for PV interconnections.
Some PV power generating and control systems use at least one of centralized inverters, bipolar centralized inverters, string inverters, and micro-inverters. Conventionally, DC/AC inverters have been used to extract maximum power from PV systems that include arrays formed by plural PV modules connected in series and parallel configurations and to convert the unregulated generated DC power to grid-voltage, synchronized AC power. The AC power generated can be transmitted and distributed either directly to AC loads or through distribution transformers. According to this method, low-voltage DC power transfer concerns and simplicity of power conversion options necessitate configuring the PV modules in serial strings and/or in parallel string arrays. However, the deleterious effects of shading, soiling, and other lighting degradation on individual PV modules and, hence, PV module characteristics matching require greater consideration.
For example, recently, the voltage at a point of common coupling (PCC) of a photovoltaic (PV) system and a power grid is regulated by controlling the amount of reactive power injected to the grid by PV. For example, proportional-integral (PI) controller has been extensively used for this regulation. However, the PI controllers with fixed gain fail to operate well in case of rapid load variations. To that end, some method proposed using PI controllers with as fuzzy logic and artificial neural networks to update the control gains according to an error between current and reference voltages. Unfortunately, modifying gains of the controllers can complicate the operation of the power grid. For example, abrupt gain change can jeopardize voltage stability and accuracy of the control, and increases the complexity of the control system. To that end, some method proposed determining gains of the controller during the offline simulations, which is a time consuming task.
Accordingly, there is a need to provide a system and a method for controlling outputs of the PV system.